Proceedings Paper

We use an algorithm based on the natural immune system for classification of aerial multispectral imagery. Our artificial immune system works by maintaining a population of detectors that remove undesired patterns, but pass a specified training set of positive examples. Any detectors reacting with input patterns are optimized to remove as many of them as possible while not removing ones similar to the training examples. This paper consists of an introduction to the natural and artificial immune systems (AIS), explanation of the AIS algorithm, results of forest and water classification using multispectral data, and discussion of sources of error and possible improvements.